Description:

The subject deals with compression methods and techniques. Main goal is to introduce basic concepts of lossless and lossy compresion of audiovisual information (entropy, redundancy and irrelevancy). Within the laboratory exercises students will work with implementations of particular algorithms, including objective and subjective methods of quality evaluation.

Contents:

1. Introduction, theory of information, entropy. Shannon-Fann coding, Huffman coding.
2. Adaptive Huffman coding, Lempel-Ziv-Welch algorithm.
3. QM coder, PPM data compression scheme.
4. Scalar quantization, optimized scalar quantization, vector quantization.
5. Human hearing, data reduction - masking, binaural hearing. Evaluation of audio quality.
6. Lossless and lossy audio compression. Filter banks, psychoacoustic model, quantization, coding, joint stereo.
7. Audio coding standards (ATRAC, Ogg Vorbis, MPEG1, MPEG2, MPEG4, MPEG7, AC3, ...).
8. Human visual system, data reduction. Evaluation of visual information quality.
9. Compression of still images, JPEG, JPEG-2000.
10. Video compression techniques: motion vector, pre & postprocessing.
11. Video coding standards, MPEG1, MPEG2, H.264/AVC, H.265/HEVC.
12. Streaming in communication networks.
13. Mobile multimedia computing. Digital content protection, watermarking.
14. New directions in audiovisual information conding, multiview coding.

Seminar contents:

1. Introduction, signal and image processing in Matlab.
2. Analysis of the characteristics of signals, the arithmetic coder.
3. Huffman coding.
4. VQ encoder. Projects assignment.
5. Implementation of simple lossy audio encoder in Matlab.
6. Subjective and objective evaluation of the quality of the compressed audio signal.
7. Compression of still pictures according to standard JPEG and JPEG-2000.
8. Principles lossy video compression, motion vector, MPEG standards.
9. subjective and objective evaluation of the quality of the compressed video signal.
10. Watermarking.
11. Work on semester project.
12. Work on semester project.
13. Presentation of semester projects.
14. Test, assessment.

Recommended literature:

[1] Proakis J.: Digital signal processing, Harlow, 2014, ISBN: 978-1-29202-573-5
[2] Thyagarajan, K. S.: Still Image and Video Compression with MATLAB, Willey, 2011, ISBN: 978-0-470-88692-2
[3] Sayood K.: Lossless Compression Handbook, Elsevier, 2003, ISBN: 978-0-12-620861-0
[4] Kahrs, M., Brandenburg, K.: Applications of Digital Signal Processing to Audio and Acoustics. Kluwer Academic Publishers, 1998, ISBN: 978-0792381303

Abbreviations used:

Semester:

• W ... winter semester (usually October - February)
• S ... spring semester (usually March - June)
• W,S ... both semesters

Mode of completion of the course:

• A ... Assessment (no grade is given to this course but credits are awarded. You will receive only P (Passed) of F (Failed) and number of credits)
• GA ... Graded Assessment (a grade is awarded for this course)
• EX ... Examination (a grade is awarded for this course)
• A, EX ... Examination (the award of Assessment is a precondition for taking the Examination in the given subject, a grade is awarded for this course)

Weekly load (hours per week):

• P ... lecture
• C ... seminar
• L ... laboratory
• R ... proseminar
• S ... seminar